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14 June 2022: Clinical Research

Fully Automatic Knee Joint Segmentation and Quantitative Analysis for Osteoarthritis from Magnetic Resonance (MR) Images Using a Deep Learning Model

Xiongfeng Tang 1ABCEF , Deming Guo 1BF , Aie Liu 2ACDE , Dijia Wu 2ADE , Jianhua Liu 3BCD , Nannan Xu 3BDF , Yanguo Qin 1ACDG*

DOI: 10.12659/MSM.936733

Med Sci Monit 2022; 28:e936733

Figure 6 The scatterplots and Bland-Altman plots show comparisons of OA-related imaging biomarkers including thickness, volumetric, joint space width, coverage for segmented structure calculations produced from manual and automatic segmentation. (A, C) Scatterplots of mean thickness of medial meniscus (MM)/lateral meniscus (LM) between manual and automatic segmentation; (B, D) Bland-Altman Plots of mean thickness of MM/LM between manual and automatic segmentation. Note that the mean difference and standard errors of the mean of the Bland-Altman plot were calculated using the entire internal dataset. (Scatterplots made by IBM SPSS Statisitc20; Bland-Altman Plots made by MedCalc Version 20.106).

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Medical Science Monitor eISSN: 1643-3750
Medical Science Monitor eISSN: 1643-3750